Sunday, January 5, 2014

In Memory MongoDB

PROBLEM:
You want to use MongoDB as an in-memory RAM-only store

SOLUTION:
You can use MongoDB and all its features as an in-memory RAM-only store! Its performance should be pretty impressive: achieving 20k writes per second, and it should scale linearly over the number of cores.
See the following great link: How to use MongoDB as a pure in-memory DB

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Sunday, September 29, 2013

What is a Product Owner?

PROBLEM:
What is a Product Owner?

SOLUTION:
Here is a short animated video on the role of the product owner.  I thought it was pretty cool so I figured I’d share it.  It’s only a few minutes.  It’s worth checking out…

http://tv.ssw.com/3244/what-is-a-product-owner

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Thursday, August 29, 2013

TFS 2010 Power Tools -- Error 1001 in Windows 8

PROBLEM:
When trying to install "Team Foundation Server Power Tools December 2011" in Windows 8, you get the following error: "Microsoft Team Foundation Server 2010 Power Tools -- Error 1001". Also, you cannot see "Process Editor" menu in Visual Studio "Tools" menu.
You already installed (by this order):
1. Visual Studio 2010
2. Visual Studio 2010 SP1

SOLUTION:
Choose custom install and do not install "Best Practice Analyzer"


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Tuesday, August 13, 2013

Use MongoDB in Windows Azure

PROBLEM:
You want to use MongoDB in Windows Azure

SOLUTION:
See the following links:

  1. MongoDB Installer for Windows on Azure
  2. Securing MongoDB on Windows Azure

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Tuesday, August 6, 2013

Performance best practices for very large tables

PROBLEM:
What are the performance best practices for very large tables?

SOLUTION:
Here is a summary of best practices for querying, monitoring, and performance tuning for your very large tables:
  • Pay attention to both the results of a query and the execution plan designed to return those results. Make it a routine exercise to scan query plans to become more familiar with how SQL Server resolves queries.
  • De-normalize your schema where possible to reduce the need to join very large tables.
  • Use table partitioning for your largest tables, and be sure when querying that the optimizer uses partition elimination whenever possible.
  • Align secondary indexes with the same table partition function to reduce partitioned table maintenance.
  • Consider using a heap instead of a clustered index, especially with a table that partially mimics a clustered index via its partition function.
  • Design indexes to be covering for larger recurring queries whenever possible, especially when creating a filtered (i.e., partial) index.
  • Use an indexed view as an alternative to a denormalized table or to materialize an aggregated dataset. The more static the underlying data, the less overhead will be required to maintain the indexed views.
  • Use summary tables with automatic (scheduled) updates as an alternative to indexed views, especially when there is less significance in the currency of the data.
  • For query monitoring, focus on the quantitative measures of Disk I/O, CPU Time, and Query Duration.
  • Use the features of the Management Data Warehouse for overall server monitoring, and use the SQL Trace data collection set for query monitoring.
  • Focus your tuning efforts on SQL code that is repeatedly run, either as a stored procedure or a SQL script, and that consumes the most server resources. Data warehouse applications tend to place the greatest pressure on Disk I/O.
  • For tuning and management of large queries, consider saving historical copies of XML execution plans to disk for later reference.


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Tuesday, June 11, 2013

MongoDB Hardware Tips

PROBLEM:
You need some hardware tips for your MongoDB installation:
  • Buy $1k 1000 servers or $10k 100 servers?
  • Fast CPU vs. more CPU cores?
  • More RAM is good?
  • Virtualization is ok?
  • SSD is good?
  • Disable NUMA (Non-Uniform Access Memory) in BIOS?
  • File system settings?
SOLUTION:
See this: https://www.youtube.com/watch?v=19VZJ9H3LmQ

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Sunday, June 9, 2013

Step by step guide for MongoDB sharding

PROBLEM:
What is a MongoDB sharded cluster?

SOLUTION:
While sharding is a powerful and compelling feature, it comes with significant infrastructure requirements and some limited complexity costs. As a result, use sharding only as necessary and when indicated by actual operational requirements.

Here is a step by step guide for MongoDB sharding:

Introduction to Sharding

Sharding Setup Demo

The config database

Setup Part 2 Adding the Initial Shards

Enabling sharding for a collection

Working with a sharded collection

Choosing shard keys

Process and Machine Layout

Bulk inserts and pre-splitting

Further tips and best practices

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